A Novel Fault Diagnosis Algorithm for the Fuel Injection System of Marine Two-Stroke Diesel Engine
- Resource Type
- Conference
- Authors
- Shi, Qingguo; Hu, Yihuai; Yan, Guohua
- Source
- 2022 7th International Conference on Power and Renewable Energy (ICPRE) Power and Renewable Energy (ICPRE), 2022 7th International Conference on. :407-412 Sep, 2022
- Subject
- Power, Energy and Industry Applications
Support vector machines
Fault diagnosis
Self-organizing feature maps
Renewable energy sources
Transducers
Diesel engines
Optimization methods
Artificial intelligence
condition monitoring
diesel engines
fault diagnosis
- Language
- ISSN
- 2768-0525
The fuel injection system plays an important role in guaranteeing the diesel engine’s power and emission along with its economical and safe usage. Current research focuses mainly on the four-stroke diesel engine, where fault diagnosis is conducted through measuring the running parameters of the fuel injection system followed by the analysis of the running conditions via feature extraction. Few studies focus on fault diagnosis for the fuel injection systems of two-stroke diesel engine. Thus, this paper investigates this domain by using three artificial intelligence algorithms: the back-propagation network, the self-organizing feature map network and support vector machine. Experimental results on the marine two-stroke diesel engine demonstrate that the support vector machine can classify the working conditions more accurately and efficiently in the case of limited samples. The accuracy rate of fault diagnosis can reach 95% when the parameters of this algorithm are optimized via the grid optimization method.